When it comes to the 2026 Bentley Supersports, paying $500,000 for less is more isn't paying more for less. More information Adding us as a Preferred Source in Google by using this link indicates that you would like to see more of our content in Google News results. Design Theme by Mulliner is Bentley's boldest specification yet, available exclusively on Supersports. It introduces the marque's first side-to-side paint fade - a bold driver-side colour blending into a darker passenger tone - carried through to a two-tone interior across three curated themes: Dragon (shown), Electric and Brodgar. "Less is more" may seem a curious phrase when applied to a half-million-dollar, 199-mph, 657-horsepower twin-turbocharged V8 brute.

Agentic LLM AI agents are often little more than autonomous chatbots: actors following scripts, often controlled by an unreliable director. This work introduces a bottom-up framework that situates AI agents in their environment, with all behaviors triggered by changes in their environments. It introduces the notion of aspects, similar to the idea of umwelt, where sets of agents perceive their environment differently to each other, enabling clearer control of information. We provide an illustrative implementation and show that compared to a typical architecture, which leaks up to 83% of the time, aspective agentic AI enables zero information leakage. We anticipate that this concept of specialist agents working efficiently in their own information niches can provide improvements to both security and efficiency.

Conversational assistants are increasingly popular across diverse real-world applications, highlighting the need for advanced multimodal speech modeling. Speech, as a natural mode of communication, encodes rich user-specific characteristics such as speaking rate and pitch, making it critical for effective interaction. Our work introduces a data-centric customization approach for efficiently enhancing multimodal understanding in conversational speech modeling. Central to our contributions is a novel multi-task learning paradigm that involves designing auxiliary tasks to utilize a small amount of speech data. Our approach achieves state-of-the-art performance on the Spoken-SQuAD benchmark, using only 10% of the training data with open-weight models, establishing a robust and efficient framework for audio-centric conversational modeling. We also introduce ASK-QA, the first dataset for multi-turn spoken dialogue with ambiguous user requests and dynamic evaluation inputs. Code and data forthcoming.

Earlier this year, Bentley stopped making the W12 that has carried its super-luxury vehicles since 2003, making way for the launch of its V8 hybrid in the new Continental GT. Now comes the second model with this potent combination: the 2025 Flying Spur. It's equipped with the same turbocharged 4.0-liter twin-turbo V8 cranking out 592 horsepower and 590 pound-feet of torque developed in conjunction with Porsche. Paired with a powerful e-motor and a 25.9 kWh battery, total output is an impressive 771 hp and 738 pound-feet of torque. In sum, Bentley calls the Flying Spur the most powerful sedan it has ever built.

It's a classic exercise in high-school art class: a student sits at her desk, charcoal pencil held in one hand, poised over a sheet of paper, while the other hand lies outstretched in front of her, palm up, fingers relaxed so that they curve inward. Then she uses one hand to draw the other. It's a beginner's assignment, but the task of depicting hands convincingly is one of the most notorious challenges in figurative art. I remember it being incredibly frustrating--getting the angles and proportion of each finger right, determining how the thumb connects to the palm, showing one finger overlapping another just so. Too often, I would end up with a bizarrely long pinky, or a thumb jutting out at an impossible angle like a broken bone.

Way back in 1985, a team of researchers at Carnegie Mellon University developed a computer purely to play games of chess. After moving to IBM, the computer was further developed, culminating in the obvious test – a match against then-world champion Garry Kasparov. However, the computer known as Deep Blue at this point wasn't enough for Kasparov; it lost four games to two. But like any good underdog, the computer was down but not out. It came back a year later to beat Kasparov in a narrow victory, winning by a single game.

If human societies are so complex, then how can we hope to understand them? Artificial Life gives us one answer. The field of Artificial Life comprises a diverse set of introspective studies that largely ask the same questions, albeit from many different perspectives: Why are we here? Who are we? Why do we behave as we do? Starting with the origins of life provides us with fascinating answers to some of these questions. However, some researchers choose to bring their studies closer to the present day. We are after all, human. It has been a few billion years since our ancestors were self-replicating molecules. Thus, more direct studies of ourselves and our human societies can reveal truths that may lead to practical knowledge. The papers in this special issue bring together scientists who choose to perform this kind of research.

Imagine a test to reliably detect an anxiety disorder or predict an impending depressive relapse that is as quick and easy as taking a temperature or measuring blood pressure. Health professionals have many tools to assess patients' physical illnesses, but not reliable biomarkers--objective indicators of health status as observed from the external part of the patient – to check mental health. However, now some researchers in artificial intelligence they believe that the sound of the voice could be the key to knowing our state of mental health… and artificial intelligence is ideal for detecting changes, which are otherwise difficult to perceive, if not impossible. The result is a series of web-based applications and tools designed to monitor our mental health status, as well as programs capable of delivering real-time mental health assessments to healthcare professionals in telemedicine and call centers. Psychologists have long known that some mental problems can be detected by listening not only to what the person says, but how do you say itsaid Maria Espinola, a psychologist and adjunct professor at the University of Cincinnati School of Medicine.

Artificial intelligence (AI) has become part of our daily life, whether through search engine algorithms or the use of Siri or Alexa on our mobile phones for translation, taxi requests or maths calculations. Businesses are taking big steps in adopting AI in their daily operations. The percentage of enterprises employing AI has grown by 270 percent over the past few years, according to Gartner, Inc. Total AI investment by firms globally surged to a record-high $77.5 billion in 2021, up from $36 billion in 2020. Its key findings reveal that the US has benefited most from this investment drive: US-based companies pulled in two-thirds of total global venture funding in AI in 2021 – or $51 billion worth of investment.

With the rapid advancement of Artificial Intelligence (AI) technology, robots equipped with Artificial Intelligence (AI) are becoming more sophisticated and capable. Neurons are like hardware and the brain is like software. People often compare the human brain to a computer. The growth of artificial intelligence and the advent of anthropomorphic robots make this metaphor even more beautiful to look at. However, Lisa Feldman-Barrett, a professor of psychology at Northeastern University in the United States, believes this similarity is problematic and may lead to misconceptions.